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从最大化似然函数获取信息AI 解读

A method is described for determining, from the maximized likelihood function, the asymptotic variance-covariance matrix of a subset of parameters. The technique is applied to the slope of a bivariate linear structural relationship.

多变量线性关系：最大似然估计与回归界限AI 解读

Summary The well known result that, when the ratio of error variances is specified in normal theory bivariate linear relationships, the maximum likelihood estimator of the slope parameter takes the same form for both structural and functional relationships is extended to the multivariate case. Furthermore, it is well known that in the bivariate case the estimator of the slope is bounded by the two regression estimators. Analogous results are derived for the multivariate…

无重复观测超结构关系的大样本性质AI 解读

Dolby (1976) introduced a model which is a synthesis of the linear structural and functional relations. The consistency of the slope estimator he proposed depends on the sequence of incidental parameters. When these parameters have finite variance the estimator is inconsistent. It is shown that a simple adjustment produces a consistent estimator of familiar form. Dolby incorrectly proposes that the asymptotic covariances of the estimators may be obtained from Fisher's…

无重复观测的超结构关系：大样本性质AI 解读

Dolby (1976) introduced a model which is a synthesis of the linear structural and functional relations. The consistency of the slope estimator he proposed depends on the sequence of incidental parameters. When these parameters have finite variance the estimator is inconsistent. It is shown that a simple adjustment produces a consistent estimator of familiar form. Dolby incorrectly proposes that the asymptotic covariances of the estimators may be obtained from Fisher's…